Daniel Kifer
Professor of Computer Science & Engineering

-
W333 Westgate
University Park, PA - duk17@psu.edu
- 814-863-1187
Huck Affiliations
Links
Publication Tags
Learning Convolutional Neural Networks Neural Networks Soil Moisture Semantics Travel Time Simulation Neurons Hydrology Big Data Moisture Trajectories Time Series Deep Learning Pixels Flow Opinion Prolongation Coding Prediction Image Compression Physics Effect Baseline LandslideMost Recent Publications
The neural coding framework for learning generative models
Alexander Ororbia, Daniel Kifer, 2022, Nature Communications
The Data Synergy Effects of Time-Series Deep Learning Models in Hydrology
Kuai Fang, Daniel Kifer, Kathryn Lawson, Dapeng Feng, Chaopeng Shen, 2022, Water Resources Research
Neural JPEG: End-to-End Image Compression Leveraging a Standard JPEG Encoder-Decoder
Ankur Mali, Alexander G. Ororbia, Daniel Kifer, C. Lee Giles, 2022, on p. 471
Free gap estimates from the exponential mechanism, sparse vector, noisy max and related algorithms
Zeyu Ding, Yuxin Wang, Yingtai Xiao, Guanhong Wang, Danfeng Zhang, Daniel Kifer, 2022, VLDB Journal
Constructing a Large-Scale Landslide Database Across Heterogeneous Environments Using Task-Specific Model Updates
Savinay Nagendra, Daniel Kifer, Benjamin Mirus, Te Pei, Kathryn Lawson, Srikanth Banagere Manjunatha, Weixin Li, Hien Nguyen, Tong Qiu, Sarah Tran, Chaopeng Shen, 2022, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing on p. 4349-4370
DPGen: Automated Program Synthesis for Differential Privacy
Yuxin Wang, Zeyu DIng, Yingtai Xiao, Daniel Kifer, Danfeng Zhang, 2021, on p. 393-411
Physics-informed deep learning for prediction of CO<sub>2</sub> storage site response
Parisa Shokouhi, Vikas Kumar, Sumedha Prathipati, Seyyed A. Hosseini, Clyde Lee Giles, Daniel Kifer, 2021, Journal of Contaminant Hydrology
Omnilayout: Room layout reconstruction from indoor spherical panoramas
Shivansh Rao, Vikas Kumar, Daniel Kifer, C. Lee Giles, Ankur Mali, 2021, on p. 3701-3710
An Empirical Analysis of Recurrent Learning Algorithms in Neural Lossy Image Compression Systems
Ankur Mali, Alexander G. Ororbia, Dan Kifer, C. Lee Giles, 2021, 2021 Data Compression Conference (DCC) on p. 356
Optimizing fitness-for-use of differentially private linear Queries
Yingtai Xiao, Zeyu Ding, Yuxin Wang, Danfeng Zhang, Daniel Kifer, 2021, Proceedings of the VLDB Endowment on p. 1730-1742
Most-Cited Papers
Pufferfish: A framework for mathematical privacy definitions
Daniel Kifer, Ashwin Machanavajjhala, 2014, ACM Transactions on Database Systems
HESS Opinions: Incubating deep-learning-powered hydrologic science advances as a community
Chaopeng Shen, Eric Laloy, Amin Elshorbagy, Adrian Albert, Jerad Bales, Fi John Chang, Sangram Ganguly, Kuo Lin Hsu, Daniel Kifer, Zheng Fang, Kuai Fang, Dongfeng Li, Xiaodong Li, Wen Ping Tsai, 2018, Hydrology and Earth System Sciences on p. 5639-5656
Prolongation of SMAP to Spatiotemporally Seamless Coverage of Continental U.S. Using a Deep Learning Neural Network
Kuai Fang, Chaopeng Shen, Daniel Kifer, Xiao Yang, 2017, Geophysical Research Letters on p. 11,030-11,039
Learning to extract semantic structure from documents using multimodal fully convolutional neural networks
Xiao Yang, Ersin Yumer, Paul Asente, Mike Kraley, Daniel Kifer, C. Lee Giles, 2017, on p. 4342-4351
Learning to read irregular text with attention mechanisms
Xiao Yang, Dafang He, Zihan Zhou, Daniel Kifer, C. Lee Giles, 2017, on p. 3280-3286
Crime rate inference with big data
Hongjian Wang, Daniel Kifer, Corina Graif, Zhenhui Li, 2016, on p. 635-644
Multi-Scale Multi-Task FCN for Semantic Page Segmentation and Table Detection
Dafang He, Scott Cohen, Brian Price, Daniel Kifer, C. Lee Giles, 2017, on p. 254-261
A Simple Baseline for Travel Time Estimation using Large-scale Trip Data
Hongjian Wang, Xianfeng Tang, Yu Hsuan Kuo, Daniel Kifer, Zhenhui Li, 2019, ACM Transactions on Intelligent Systems and Technology
Multi-scale FCN with cascaded instance aware segmentation for arbitrary oriented word spotting in the wild
Dafang He, Xiao Yang, Chen Liang, Zihan Zhou, Alex G. Ororbia, Daniel Kifer, C. Lee Giles, 2017, on p. 474-483
A neural temporal model for human motion prediction
Anand Gopalakrishnan, Ankur Mali, Dan Kifer, Lee Giles, Alexander G. Ororbia, 2019, on p. 12108-12117